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Progress on the research of species delimitation based on Bayesian model selection
Update time: 2019-05-13

Recently, scientists from Academy of Mathematics and Systems Science (AMSS) made progress on the Bayesian molecular delimitation. The work is published in Systematic Biology, a top journal in the field of evolution and ecology. This work was collaborated with scientists from UC Davis and University of Seattle. Dr. Tianqi Zhu and Prof. Ziheng Yang (a guest professor of AMSS) are a first author and the corresponding author of this work.

Species delimitation is a basic problem of taxonomy. BPP, the most widely used molecular dating software, is developed based on the Bayesian model selection method. Recent simulation studies examining the performance of Bayesian species delimitation as implemented in the BPP program have suggested that BPP may detect population splits but not species divergences and that it tends to oversplit when data of many loci are analyzed. Here, they confirm these results and provide the mathematical justifications. They point out that the distinction between population and species splits made in the protracted speciation model (PSM) has no influence on the generation of gene trees and sequence data, which explains why no method can use such data to distinguish between population splits and speciation. They suggest that the PSM is unrealistic as its mechanism for assigning species status assumes instantaneous speciation, contradicting prevailing taxonomic practice. They confirm the suggestion, based on simulation, that in the case of speciation with gene flow, Bayesian model selection as implemented in BPP tends to detect population splits when the amount of data (the number of loci) increases.

They discuss the use of a recently proposed empirical genealogical divergence index (gdi) for species delimitation and illustrate that parameter estimates produced by a full likelihood analysis as implemented in BPP provide much more reliable inference under the gdi than the approximate method PHRAPL. They distinguish between Bayesian model selection and parameter estimation and suggest that the model selection approach is useful for identifying sympatric cryptic species, while the parameter estimation approach may be used to implement empirical criteria for determining species status among allopatric populations.

A traditional Chinese painting of loquat, imitating a phylogenetic tree with radiative evolution. Confusion between loquat and kumquats dates back to Song Dynasty.



Leache AD, Zhu T, Rannala B, Yang Z. 2019. The spectre of too many species. Syst Biol. 68: 168-181.



Tianqi Zhu  


Academy of Mathematics and Systems Science, CAS 

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